Research ArticleAtherosclerosis

Detecting human coronary inflammation by imaging perivascular fat

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Science Translational Medicine  12 Jul 2017:
Vol. 9, Issue 398, eaal2658
DOI: 10.1126/scitranslmed.aal2658
  • Fig. 1. Phenotyping of human adipose tissue.

    Representative bright-field microscopic images of human (A) EpAT, (B) ThAT, and (C) ScAT. (D) Adipocyte size (n = 5 patients) and (E) adipocytes per field (n = 6 patients), quantified from tissue sections of EpAT, ThAT, and ScAT from the same patients. (F) Adipocyte size correlated with FABP4 expression (n = 16). (G) Gene expression of PPAR-γ, (H) CEBPA, (I) and FABP4 (samples from n = 433 patients). Ptrend derived from repeated-measures analysis of variance (ANOVA) with Bonferroni correction (D), Friedman’s test with Dunn’s post hoc correction (E), or Kruskal-Wallis with Dunn’s post hoc correction (G to I) *P < 0.05, **P < 0.01, ***P < 0.001 versus ScAT.

  • Fig. 2. Vascular inflammation blocks perivascular adipocyte differentiation through paracrine signals.

    (A) Experimental design of the coculture experiments in study arm 2. Human aortic tissue (Ao) from 15 patients undergoing CABG was harvested and cultured for 7 days ± angiotensin II (AngII; 100 nM). Preadipocytes isolated from PVAT around the right coronary artery (RCA) were also cultured for this period. After 7 days, the aortic tissue was washed to remove angiotensin II and was cocultured with the preadipocytes before a differentiation time course was induced. (B) IL-6, TNF-α, and IFN-γ gene expression in aortic tissue before and after stimulation with angiotensin II (n = 5 to 7 per group). (C) Quantification of oil red O in preadipocytes (control) or preadipocytes co-incubated with aortic tissue or aortic tissue prestimulated with angiotensin II (n = 6 per group). (D to F) Representative images of oil red O staining in preadipocytes co-incubated with aortic tissue as in (C). P values derived from Wilcoxon signed-rank test (B) and repeated-measures ANOVA followed by individual comparisons using paired t test (C). *P < 0.05, **P < 0.001 versus control.

  • Fig. 3. Cytokines trigger proliferation and block differentiation of perivascular adipocytes.

    In study arm 2, human preadipocytes were isolated from PVAT around the RCA and differentiated in the presence or absence of inflammatory cytokines [recombinant TNF-α (4 ng/ml) + IL-6 (25 ng/ml) + IFN-γ (20 ng/ml)] until day 9 of differentiation [(A and B) without cytokines and (C and D) with cytokines, oil red O staining at day 9 of differentiation]. (E) Oil red O photometric quantification of lipid accumulation in preadipocytes differentiated with and without cytokines (n = 7). Effects of cytokines on (F) preadipocyte proliferation and gene expression of the differentiation markers (G) PPAR-γ, (H) CEBPA, and (I) FABP4 (n = 3 independent experiments in triplicate). P values derived from Wilcoxon signed-rank test (E) or two-way ANOVA with “time × treatment” interaction (F to I).

  • Fig. 4. Ex vivo characterization of adipocyte size and adipogenesis using CT.

    Explants of EpAT, ThAT, and ScAT from patients undergoing CABG (study arm 1) were scanned by CT to calculate FAI for each sample. Association of FAI with the expression of (A to C) CEBPA (EpAT, n = 87; ThAT, n = 311; ScAT, n = 288) and (D to F) FABP4 (EpAT, n = 85; ThAT, n = 312; ScAT, n = 259) genes in all depots. (G) Correlation between adipocyte size and FAI (n = 44 biopsies). Association between FAI measured in vivo and in explants of (H) EpAT and (I) ScAT collected from 105 patients in study arm 1. P values by Kruskal-Wallis (A to F) and one-way ANOVA (H and I).

  • Fig. 5. In vivo characterization of adipogenesis by CT.

    Association of in vivo FAI for EpAT and ScAT of patients undergoing CT with gene expression of (A and B) CEBPA and (C and D) FABP4 by the same adipose tissue samples collected from the same patients during surgery (study arm 1). (E) Comparison of in vivo FAI between EpAT and ScAT and (F) associations with systemic insulin resistance. P values by Kruskal-Wallis (A to D) or Wilcoxon signed-rank test (E) or one-way ANOVA (F). NS, Not significant. Studies were performed in the 105 patients from the in vivo CTA group of study arm 1.

  • Fig. 6. FAI for the detection of human adipose tissue inflammation by noninvasive imaging.

    Associations between CEBPA gene expression and CCR7/MRC1 gene expression ratio in (A) ScAT (n = 267) or (B) EpAT (n = 207) adipose tissue in study arm 1. (C) Correlations between 18FFDG uptake of ScAT by PET/CT [determined as the mean tissue-to-background ratio (TBR)] with FAI of the same tissue (n = 39) and (D) receiver operating characteristic curves for identification of highly inflamed ScAT by FAI according to 18FFDG uptake measured by PET/CT. (E) Representative examples of FAI and 18FFDG uptake heat maps in ScAT. P values by Kruskal-Wallis test (A and B). SUV, standardized uptake value.

  • Fig. 7. Gradient of adipocyte size and FAI around the human coronaries in the presence or absence of coronary atherosclerosis.

    (A) PPAR-γ, (B) CEBPA, and (C) CEBPA4 gene expression and (D) adipocyte size in pericoronary adipose tissue samples attached to the RCA and paired samples ~20 mm away from it [n = 6 to 12 pairs for (A) to (D)]. (E to G) In study arm 3, FAI around the RCA of patients undergoing CTA was calculated for each cylindrical 1-mm-thick layer of pericoronary tissue, whereas for a radial distance, FAI was calculated from RCA wall 1 to 20 mm. (H) FAI mapping of PVAT around the RCA. (I) FAI and radial distance from vascular wall in patients with CAD (n = 149) versus healthy individuals (n = 117) [comparison of the area under the curve (AUC) using unpaired t test and comparison of the curves using two-way ANOVA for repeated measures with “FAI × distance” interaction]. P values by Wilcoxon signed-rank test (A to D).

  • Fig. 8. FAIPVAT and VPCI as novel phenotyping tools for vascular disease.

    (A) Associations between FAIPVAT/FAInon-PVAT and CAD. (B and C) Association between calcification volume and FAIPVAT or VPCI. (D and E) Both FAIPVAT and VPCI are related with atherosclerotic plaque burden in RCA [n = 267 for (A) to (E)]. (F) Comparisons of FAIPVAT and VPCI between noncalcified plaques (n = 26) and mixed or calcified plaques (n = 84) in CAD patients with high atherosclerotic plaque burden in the RCA (defined as >33rd percentile). (G) Changes in FAIPVAT around ruptured (culprit) atherosclerotic lesions (n = 10) of acute MI patients, nonculprit lesions of the same patients (n = 7), or lesions in stable CAD patients (n = 13); Δ[FAIPVAT] = FAIPVAT(around lesion) – FAIPVAT(proximal segment). (H) Comparison of Δ[FAIPVAT] between stable and unstable plaques and (I) its diagnostic accuracy in receiver operator characteristic (ROC) curve analysis for detection of unstable plaques (culprit lesions). (J) Paired CT scans with 5 weeks difference, to assess temporal changes of FAIPVAT in acute MI and stable CAD patients (n = 5). (K) Representative images of FAIPVAT color maps around: (i) a culprit lesion (green arrowheads, identified by the presence of the stent, upper left image), (ii) a nonculprit lesion from the same patient (identified by the presence of the stent implanted in the same session as the culprit, upper right image), (iii) a stable atherosclerotic lesion without a stent (lower left image), and (iv) a stent implanted at least 3 months before imaging (lower right image); green arrowheads flag the plaque/stent. (L) A schematic representation of the study’s findings that translate the inside-to-outside signal from the human coronaries to their PVAT into an imaging application. P values derived from unpaired t test (A, F, and H), one-way ANOVA (B to E), two-way ANOVA (G), or Wilcoxon signed-rank test (J).

Supplementary Materials

  • www.sciencetranslationalmedicine.org/cgi/content/full/9/398/eaal2658/DC1

    Materials and Methods

    Fig. S1. Study flow chart.

    Fig. S2. Adipocyte differentiation in vitro and lipid accumulation.

    Fig. S3. Effects of proinflammatory cytokines on preadipocyte differentiation.

    Fig. S4. FAI and macrophage infiltration and polarization status in adipose tissue explants.

    Fig. S5. Gene expression of inflammatory cytokines and markers of macrophage infiltration/polarization in coronary PVAT versus non-PVAT.

    Fig. S6. Variation in FAI mapping of pericoronary adipose tissue in the absence of vascular disease.

    Fig. S7. FAIPVAT and CAD.

    Fig. S8. Associations between EpAT and PVAT volumes and coronary atherosclerosis/calcification.

    Fig. S9. Associations between coronary PVAT imaging phenotyping and coronary calcium score.

    Fig. S10. Correlations between FAIPVAT and coronary plaque burden in major epicardial arteries.

    Fig. S11. Detection of noncalcified plaques in human coronaries by CT imaging mapping of pericoronary adipose tissue.

    Fig. S12. Technical considerations related to calculation of FAI.

    Table S1. Demographic characteristics of study participants.

    Table S2. Range of FAI values in adipose tissue explants and in vivo.

    Table S3. Demographic characteristics of study participants in study arms 3 and 4.

    Table S4. Predictive value of FAIPVAT to describe CAD and atherosclerotic plaque burden independently of coronary calcium score.

    Table S5. Individual subject-level data.

  • Supplementary Material for:

    Detecting human coronary inflammation by imaging perivascular fat

    Alexios S. Antonopoulos, Fabio Sanna, Nikant Sabharwal, Sheena Thomas, Evangelos K. Oikonomou, Laura Herdman, Marios Margaritis, Cheerag Shirodaria, Anna-Maria Kampoli, Ioannis Akoumianakis, Mario Petrou, Rana Sayeed, George Krasopoulos, Constantinos Psarros, Patricia Ciccone, Carl M. Brophy, Janet Digby, Andrew Kelion, Raman Uberoi, Suzan Anthony, Nikolaos Alexopoulos, Dimitris Tousoulis, Stephan Achenbach, Stefan Neubauer, Keith M. Channon, Charalambos Antoniades*

    *Corresponding author. Email: antoniad{at}well.ox.ac.uk

    Published 12 July 2017, Sci. Transl. Med. 9, eaal2658 (2017)
    DOI: 10.1126/scitranslmed.aal2658

    This PDF file includes:

    • Materials and Methods
    • Fig. S1. Study flow chart.
    • Fig. S2. Adipocyte differentiation in vitro and lipid accumulation.
    • Fig. S3. Effects of proinflammatory cytokines on preadipocyte differentiation.
    • Fig. S4. FAI and macrophage infiltration and polarization status in adipose tissue explants.
    • Fig. S5. Gene expression of inflammatory cytokines and markers of macrophage infiltration/polarization in coronary PVAT versus non-PVAT.
    • Fig. S6. Variation in FAI mapping of pericoronary adipose tissue in the absence of vascular disease.
    • Fig. S7. FAIPVAT and CAD.
    • Fig. S8. Associations between EpAT and PVAT volumes and coronary atherosclerosis/calcification.
    • Fig. S9. Associations between coronary PVAT imaging phenotyping and coronary calcium score.
    • Fig. S10. Correlations between FAIPVAT and coronary plaque burden in major epicardial arteries.
    • Fig. S11. Detection of noncalcified plaques in human coronaries by CT imaging mapping of pericoronary adipose tissue.
    • Fig. S12. Technical considerations related to calculation of FAI.
    • Table S1. Demographic characteristics of study participants.
    • Table S2. Range of FAI values in adipose tissue explants and in vivo.
    • Table S3. Demographic characteristics of study participants in study arms 3 and 4.
    • Table S4. Predictive value of FAIPVAT to describe CAD and atherosclerotic plaque burden independently of coronary calcium score.
    • Table S5. Individual subject-level data.

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